Robust Particle Swarm toolbox implementing Trelea, Common, and Clerc types along with an alpha version of change detection.
This toolbox is designed for researchers in Computational Intelligence as well as application developers, students, and classroom labs. It is robust enough that several papers have been developed using it but it is also in constant development and very easy to hack. Users of MATLAB's Optimization Toolbox should feel right at home but even if you don't use that toolbox this will be easy to figure. Extensive help is included.
Anyone from serious AI researchers to beginning students should get something out of this.
This toolbox is constantly evolving and I welcome suggestions.
Current feature set:
* Trelea, Clerc, and Common Types
* Vectorized and non-vectorized versions, you can investigate thousands of particles at once with the proper cost function.
* custom plotting plug ins
* neural net trainer (requires Matlab's neural net toolbox)
* PDF Particle Swarm Introduction
* Alpha version of change detection, will track dynamic environments
* includes suite of test functions commonly used in the CI/optimization community.
Brian Birge (2024). Particle Swarm Optimization Toolbox (https://www.mathworks.com/matlabcentral/fileexchange/7506-particle-swarm-optimization-toolbox), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
- AI, Data Science, and Statistics > Deep Learning Toolbox >
- Mathematics and Optimization > Global Optimization Toolbox > Direct Search >
- Mathematics and Optimization > Global Optimization Toolbox > Particle Swarm >
- MATLAB > Mathematics > Graph and Network Algorithms > Shortest Path > Traveling Salesman (TSP) >
Inspired: PSO solution to economic dispatch, Improved PSO program to solve Economic Dispatch, Constrained Particle Swarm Optimization, Neural Network add-in for PSORT, Optimal Power Flow by Vector PSO
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Added neural net trainer plugin, some bug fixes, updated graphical routines, the neural net trainer part requires Matlab's Neural Net Toolbox, but everything else is standalone.